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𝐄𝐥𝐢𝐠𝐢𝐛𝐢𝐥𝐢𝐭𝐲 𝐂𝐫𝐢𝐭𝐞𝐫𝐢𝐚

2-5 yrs of proven experience in ML, DL, and preferably NLP.

Preferred Educational Background - B.E/B.Tech, M.S./M.Tech, Ph.D.


𝐖𝐡𝐚𝐭 𝐰𝐢𝐥𝐥 𝐲𝐨𝐮 𝐰𝐨𝐫𝐤 𝐨𝐧?
𝟏) Problem formulation and solution designing of ML/NLP applications across complex well-defined as well as open-ended healthcare problems.
2) Cutting-edge machine learning, data mining, and statistical techniques to analyse and utilise large-scale structured and unstructured clinical data.
3) End-to-end development of company proprietary AI engines - data collection, cleaning, data modelling, model training / testing, monitoring, and deployment.
4) Research and innovate novel ML algorithms and their applications suited to the problem at hand.


𝐖𝐡𝐚𝐭 𝐚𝐫𝐞 𝐰𝐞 𝐥𝐨𝐨𝐤𝐢𝐧𝐠 𝐟𝐨𝐫?
𝟏) Deeper understanding of business objectives and ability to formulate the problem as a Data Science problem.
𝟐) Solid expertise in knowledge graphs, graph neural nets, clustering, classification.
𝟑) Strong understanding of data normalization techniques, SVM, Random forest, data visualization techniques.
𝟒) Expertise in RNN, LSTM, and other neural network architectures.
𝟓) DL frameworks: Tensorflow, Pytorch, Keras
𝟔) High proficiency with standard database skills (e.g., SQL, MongoDB, Graph DB), data preparation, cleaning, and wrangling/munging.
𝟕) Comfortable with web scraping, extracting, manipulating, and analyzing complex, high-volume, high-dimensionality data from varying sources.
𝟖) Experience with deploying ML models on cloud platforms like AWS or Azure.
9) Familiarity with version control with GIT, BitBucket, SVN, or similar.


𝐖𝐡𝐲 𝐜𝐡𝐨𝐨𝐬𝐞 𝐮𝐬?
𝟏) We offer Competitive remuneration.
𝟐) We give opportunities to work on exciting and cutting-edge machine learning problems so you contribute towards transforming the healthcare industry.
𝟑) We offer flexibility to choose your tools, methods, and ways to collaborate.
𝟒) We always value and believe in new ideas and encourage creative thinking.
𝟓) We offer open culture where you will work closely with the founding team and have the chance to influence the product design and execution.
𝟔) And, of course, the thrill of being part of an early-stage startup, launching a product, and seeing it in the hands of the users.

ML Engineer
WE ARE GRAPHENE

Graphene is an award-winning AI company, developing customized insights and data solutions for corporate clients. With a focus on healthcare, consumer goods and financial services, our proprietary AI platform is disrupting market research with an approach that allows us to get into the mind of customers to a degree unprecedented in traditional market research.

Graphene was founded by corporate leaders from Microsoft and P&G and works closely with the Singapore Government & universities in creating cutting edge technology. We are gaining traction with many Fortune 500 companies globally.

Graphene has a 6-year track record of delivering financially sustainable growth and is one of the few start-ups which are self-funded, yet profitable and debt free.

We already have a strong bench strength of leaders in place. Now, we are looking to groom more talents for our expansion into the US. Join us and take both our growths to the next level!

 

 

• Primary Purpose: As part of a highly productive and creative AI (NLP) analytics team, optimize algorithms/models for performance and scalability, engineer & implement machine learning algorithms into services and pipelines to be consumed at web-scale
• Daily Grind: Interface with data scientists, project managers, and the engineering team to achieve sprint goals on the product roadmap, and ensure healthy models, endpoints, CI/CD,
• Career Progression: Senior ML Engineer, ML Architect

 

• Work in a product-development team capable of independently authoring software products.
• Guide junior programmers, set up the architecture, and follow modular development approaches.
• Design and develop code which is well documented.
• Optimize of the application for maximum speed and scalability
• Adhere to the best Information security and Devops practices.
• Research and develop new approaches to problems.
• Design and implement schemas and databases with respect to the AI application
• Cross-pollinated with other teams.

 

HARD AND SOFT SKILLS

Must Have

• Problem-solving abilities
• Extremely strong programming background – data structures and algorithm
• Advanced Machine Learning: TensorFlow, Keras
• Python, spaCy, NLTK, Word2Vec, Graph databases, Knowledge-graph, BERT (derived models), Hyperparameter tuning
• Experience with OOPs and design patterns
• Exposure to RDBMS/NoSQL
• Test Driven Development Methodology

 

Good to Have

• Working in cloud-native environments (preferably Azure)
• Microservices
• Enterprise Design Patterns
• Microservices Architecture
• Distributed Systems